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   "execution_count": null,
   "id": "4e2a9393-7767-488e-a8bf-27c12dca35bd",
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   "source": [
    "# imports\n",
    "\n",
    "import os\n",
    "import requests\n",
    "from dotenv import load_dotenv\n",
    "from bs4 import BeautifulSoup\n",
    "from IPython.display import Markdown, display\n",
    "from openai import OpenAI\n",
    "\n",
    "# If you get an error running this cell, then please head over to the troubleshooting notebook!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b87cadb-d513-4303-baee-a37b6f938e4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load environment variables in a file called .env\n",
    "\n",
    "load_dotenv(override=True)\n",
    "api_key = os.getenv('OPENAI_API_KEY')\n",
    "\n",
    "# Check the key\n",
    "\n",
    "if not api_key:\n",
    "    print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
    "elif not api_key.startswith(\"sk-proj-\"):\n",
    "    print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n",
    "elif api_key.strip() != api_key:\n",
    "    print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
    "else:\n",
    "    print(\"API key found and looks good so far!\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "019974d9-f3ad-4a8a-b5f9-0a3719aea2d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "openai = OpenAI()\n",
    "\n",
    "# If this doesn't work, try Kernel menu >> Restart Kernel and Clear Outputs Of All Cells, then run the cells from the top of this notebook down.\n",
    "# If it STILL doesn't work (horrors!) then please see the Troubleshooting notebook in this folder for full instructions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f4484fcf-8b39-4c3f-9674-37970ed71988",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 1: Create your prompts\n",
    "\n",
    "system_prompt = f\"\"\"\n",
    "                You are an assistant that will analyze the ratings & reviews from :\\n\\n{reviews_text}\\n\\n and comeup with a summary of how many 5,4,3,2,1 star rating the restuarnat has. \n",
    "                You will also come up with a summary of the reviews showing what the customers love about the restaurant and what they dont like. Also extract the name of the restaurant,\n",
    "                the location and the cuisine. Respond in markdown\"\"\"\n",
    "user_prompt = \"This is the summary for the restaurant: \"\n",
    "\n",
    "# Step 2: Make the messages list\n",
    "\n",
    "messages = [\n",
    "     {\"role\": \"system\", \"content\": system_prompt},\n",
    "     {\"role\": \"user\", \"content\": user_prompt}\n",
    "] \n",
    "\n",
    "def generate_review_summary(reviews_text):\n",
    "    response = openai.chat.completions.create(\n",
    "        model = \"gpt-4o-mini\",\n",
    "        messages = messages\n",
    "    )\n",
    "    return response.choices[0].message.content\n",
    "\n",
    "try:\n",
    "    with open('restaurant_reviews.txt', 'r') as file:\n",
    "        reviews_text = file.read()\n",
    "    \n",
    "    # Generate review summary\n",
    "    summary = generate_review_summary(reviews_text)\n",
    "    display(Markdown(summary))\n",
    "\n",
    "except FileNotFoundError:\n",
    "    print(\"The specified reviews file was not found. Please ensure 'restaurant_reviews.txt' is in the correct directory.\")"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "id": "3eccbf35-0a0b-4a1b-b493-aa5c342109cc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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